Efficient disparity vector coding for multi-view 3-D displays

Disparity estimation can be used for eliminating redundancies between different views of an object or a scene recorded by an array of cameras which are arranged both horizontally and vertically. However, estimation of the disparity vectors is a highly time consuming process which takes most of the operation time of the multi-view video coding. Therefore, either the amount of data that is to be processed or the complexity of the coding method needs to be decreased in order to encode the multi-view video in a reasonable time. It is proven that the disparities of a point in the scene photographed by cameras which are spaced equidistantly are equal. Since there is a strong geometrical correlation of the disparity vectors, the disparity vector of a view can for most blocks be derived from the disparity vector of another view or views. A new algorithm is presented that reduces the amount of processing time needed for calculating the disparity vectors of each neighboring view except the principal ones. Different schemes are proposed for 3*3 views and they are applied to several image sequences taken from a camera-array. The experimental results show that the proposed schemes yield better results than the reference scheme while preserving the image quality and the amount of encoded data.Disparity estimation can be used for eliminating redundancies between different views of an object or a scene recorded by an array of cameras which are arranged both horizontally and vertically. However, estimation of the disparity vectors is a highly time consuming process which takes most of the operation time of the multi-view video coding. Therefore, either the amount of data that is to be processed or the complexity of the coding method needs to be decreased in order to encode the multi-view video in a reasonable time. It is proven that the disparities of a point in the scene photographed by cameras which are spaced equidistantly are equal. Since there is a strong geometrical correlation of the disparity vectors, the disparity vector of a view can for most blocks be derived from the disparity vector of another view or views. A new algorithm is presented that reduces the amount of processing time needed for calculating the disparity vectors of each neighboring view except the principal ones. Different schemes are proposed for 3*3 views and they are applied to several image sequences taken from a camera-array. The experimental results show that the proposed schemes yield better results than the reference scheme while preserving the image quality and the amount of encoded data.P